Purpose The purpose of this paper is to investigate the thermomechanical behavior of stainless steel AISI 304L during rolling at elevated temperatures. Design/methodology/approach Two-dimensional finite element analysis together with the upper-bound solution were used for predicting temperature field and required power in warm and hot rolling operations. The required power and heat of deformation were estimated employing an upper-bound solution based on cylindrical velocity field and at the same time, temperature distributions within the rolling steel and the work rolls were determined by means of a thermal finite element analysis. To consider the effect of flow stress and its dependence on temperature, strain and strain rate, a neural network model was used and combined with the thermal and mechanical models. Finally, the microstructure of rolled steel was studied and the effect of rolling conditions was justified employing the predictions. Findings The results have shown that the predicted temperature variations were in good agreement with the experiments. Moreover, the model was shown to be capable of determining the effects of various rolling parameters such as reduction and rolling speed with low-computational cost as well as reasonable accuracy. Originality/value A combined upper-bound finite element analysis was developed to predict the required power and temperature field during plate rolling while the model can be employed under both hot and warm rolling conditions.

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